The first uses of SOM neural networks for the prediction of a time series, here representing deterministic chaos. In the video the dots represent the reference vectors of the SOM neurons in the first 3 dimensions of the time delay embedding. After random initialization, the dots represent the attractor of the Mackey-Glass time series, with the embedding time delay parameter Delta=6. The data generation process used the chaos determination parameter tau=16 (quasi periodic curve resembling the double looped double filament) and tau=17 (the attractor gets chaotic with fractal dimension 2.1). More details in Dimplomarbeit (in german).

Unimate PUMA classical industrial robot follows a ball. An end-effector mounted camera and a "wrist" 6D-force-torque sensor are used for the tracking algorithm. Pulling and pushing is sensed at the wrist, therefore the reaction is soft below and stiff at the arm above the sensor.
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